{"id":"W4391302634","doi":"10.2514/6.2024-0261","title":"Neural Network Adaptive Controller with Approximate Dynamic Inversion for the Cessna Citation X Lateral Control","year":2024,"lang":"en","type":"article","venue":"","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Inversion (geology); Artificial neural network; Adaptive control; Computer science; Control theory (sociology); Controller (irrigation); Control (management); Artificial intelligence; Geology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003818244,0.0005217653,0.0003297947,0.0002363469,0.0003862816,0.0005260811,0.0006773568,0.0004576116,0.001791038],"category_scores_gemma":[0.0006150579,0.0001505295,0.0003283168,0.0001990704,0.0003116612,0.000297322,0.0004109159,0.0007328371,0.0003381955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004126834,"about_ca_system_score_gemma":0.0005193957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005995553,"about_ca_topic_score_gemma":0.00595349,"domain_scores_codex":[0.9997881,0.00002787576,0.00001299161,0.00005211136,0.00009915544,0.0000197424],"domain_scores_gemma":[0.9998585,0.00003694226,0.00002395919,0.00001070255,0.00006428858,0.000005674288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002815126,0.0001307573,0.00139032,0.0003203455,0.00008464845,0.0002207211,0.0002494335,0.6007915,0.07095254,0.008657153,0.001750949,0.3151701],"study_design_scores_gemma":[0.00001477155,0.0001533835,0.0003726944,0.0000124901,0.00001525979,0.00004195084,0.00001418129,0.9916568,0.005026691,0.000380981,0.002300435,0.00001043561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02980701,0.0004844605,0.9600213,0.000105349,0.0001012573,0.00008373245,0.00001585471,0.0005642551,0.008816713],"genre_scores_gemma":[0.8991182,0.0003379252,0.09058619,0.0001052106,0.00005798828,0.0002071128,0.00005337788,0.00002858387,0.009505445],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005995553,"threshold_uncertainty_score":0.01192129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0114294499579065,"score_gpt":0.21410460862622,"score_spread":0.2026751586683135,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}